LLM Research Engineer (NLP)

Team: Digital

Location: Kyiv, Ukraine

Commitment: Full-Time (Full Remote)

Workplace Type: remote

What you will do

• Curation of datasets for pre-training, supervised fine-tuning, and alignment
• Research and develop best practices and novel techniques in LLM training and evaluation pipelines.
• Collaborate closely with data engineers, annotators, linguists, and domain experts to scale data processes, define evaluation tasks and collect high-quality feedback.

Qualifications and experience needed

• Education & Experience:
• 3+ years of experience in Data Science or Machine Learning, preferably with a focus on NLP.
• An advanced degree (Master’s or PhD) in Computer Science, Computational Linguistics, Machine Learning, or a related field is highly preferred.
• GenAI & NLP Expertise:
• Practical experience with fine-tuning LLMs / VLMs models
• Hands-on experience with modern NLP approaches, including embedding models, semantic search, text classification, sequence tagging (NER), transformers/LLMs, RAGs.
• ML & Programming Skills:
• Strong experience with deep learning frameworks such as PyTorch or JAX for building models.
• Ability to write efficient, clean code and debug complex model issues.

A plus would be

• Advanced NLP/ML Techniques:
• Applied experience using Reinforcement Learning in NLP / LLM settings
• Prior work on LLM safety, fairness, and bias mitigation.
• Experience generating and curating synthetic datasets for Supervised Fine-Tuning (SFT), including quality control and scaling considerations.
• Research & Community:
• Publications in NLP/ML conferences or contributions to open-source NLP projects.
• Active participation in the AI community or demonstrated continuous learning (e.g., Kaggle competitions, research collaborations) indicates a passion for staying at the forefront of the field.
• MLOps & Infrastructure:
• Hands-on experience with containerization (Docker) and orchestration (Kubernetes) for ML, as well as ML workflow tools (MLflow, Airflow).
• Experience in working alongside MLOps engineers to streamline the deployment and monitoring of NLP models.
• Experience with cloud platforms (AWS, GCP, or Azure) and big data technologies (Spark, Hadoop, Ray, Dask) for scaling data processing or model training is a plus.
• Problem-Solving:
• Innovative mindset with the ability to approach open-ended AI problems creatively.
• Comfort in a fast-paced R&D environment where you can adapt to new challenges, propose solutions, and drive them to implementation

What we offer

• Office or remote — it’s up to you. You can work from anywhere, and we will arrange your workplace
• Remote onboarding
• We train employees with the opportunity to learn through the company’s library, internal resources, and programs from partners
• Health and life insurance
• Wellbeing program and corporate psychologist
• Reimbursement of expenses for Kyivstar mobile communication